Background To date, few data on paediatric COVID-19 have been published, and most reports originate from China. This study aimed to capture key data on children and adolescents with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection across Europe to inform physicians and health-care service planning during the ongoing pandemic. Methods This multicentre cohort study involved 82 participating health-care institutions across 25 European countries, using a well established research network-the Paediatric Tuberculosis Network European Trials Group (ptbnet)-that mainly comprises paediatric infectious diseases specialists and paediatric pulmonologists. We included all individuals aged 18 years or younger with confirmed SARS-CoV-2 infection, detected at any anatomical site by RT-PCR, between April 1 and April 24, 2020, during the initial peak of the European COVID-19 pandemic. We explored factors associated with need for intensive care unit (ICU) admission and initiation of drug treatment for COVID-19 using univariable analysis, and applied multivariable logistic regression with backwards stepwise analysis to further explore those factors significantly associated with ICU admission. Findings 582 individuals with PCR-confirmed SARS-CoV-2 infection were included, with a median age of 5•0 years (IQR 0•5-12•0) and a sex ratio of 1•15 males per female. 145 (25%) had pre-existing medical conditions. 363 (62%) individuals were admitted to hospital. 48 (8%) individuals required ICU admission, 25 (4%) mechanical ventilation (median duration 7 days, IQR 2-11, range 1-34), 19 (3%) inotropic support, and one (<1%) extracorporeal membrane oxygenation. Significant risk factors for requiring ICU admission in multivariable analyses were being younger than 1 month (odds ratio 5•06, 95% CI 1•72-14•87; p=0•0035), male sex (2•12, 1•06-4•21; p=0•033), pre-existing medical conditions (3•27, 1•67-6•42; p=0•0015), and presence of lower respiratory tract infection signs or symptoms at presentation (10•46, 5•16-21•23; p<0•0001). The most frequently used drug with antiviral activity was hydroxychloroquine (40 [7%] patients), followed by remdesivir (17 [3%] patients), lopinavir-ritonavir (six [1%] patients), and oseltamivir (three [1%] patients). Immunomodulatory medication used included corticosteroids (22 [4%] patients), intravenous immunoglobulin (seven [1%] patients), tocilizumab (four [1%] patients), anakinra (three [1%] patients), and siltuximab (one [<1%] patient). Four children died (case-fatality rate 0•69%, 95% CI 0•20-1•82); at study end, the remaining 578 were alive and only 25 (4%) were still symptomatic or requiring respiratory support. Interpretation COVID-19 is generally a mild disease in children, including infants. However, a small proportion develop severe disease requiring ICU admission and prolonged ventilation, although fatal outcome is overall rare. The data also reflect the current uncertainties regarding specific treatment options, highlighting that additional data on antiviral and immunomodulatory drugs...

SummaryThere are no epidemiological studies from the British Isles of chronic granulomatous disease, characterized by recurrent, life-threatening bacterial and fungal infections and inflammatory sequelae. Patients were enrolled in a national registry and medical records were analysed. Of 94 subjects, 69 had X-linked disease, 16 had autosomal recessive disease and nine were unknown. Prevalence was 7·5/million for 1990-99 and 8·5/million for 1980-89. Suppurative adenitis, abscesses and pneumonia presented commonly. Twenty-three of 30 patients who underwent high resolution computerized tomography had chronic respiratory disease. Inflammatory sequelae included bowel stricture and urogenital tract granulomata. Growth failure was common; 75% of those measured were below the population mean. All patients received prophylactic antibiotics and 93% anti-fungal prophylaxis. Interferon gamma was used to treat infection, but rarely as prophylaxis. Despite prophylaxis, estimated survival was 88% at 10 years but 55% at age 30 years. Morbidity remains significant, severe infectious complications common. Curative treatments including stem cell transplantation should be considered for patients with frequent or serious complications.

IMPORTANCEThe National COVID Cohort Collaborative (N3C) is a centralized, harmonized, highgranularity electronic health record repository that is the largest, most representative COVID-19 cohort to date. This multicenter data set can support robust evidence-based development of predictive and diagnostic tools and inform clinical care and policy.OBJECTIVES To evaluate COVID-19 severity and risk factors over time and assess the use of machine learning to predict clinical severity. DESIGN, SETTING, AND PARTICIPANTSIn a retrospective cohort study of 1 926 526 US adults with SARS-CoV-2 infection (polymerase chain reaction >99% or antigen <1%) and adult patients without SARS-CoV-2 infection who served as controls from 34 medical centers nationwide between January 1, 2020, and December 7, 2020, patients were stratified using a World Health Organization COVID-19 severity scale and demographic characteristics. Differences between groups over time were evaluated using multivariable logistic regression. Random forest and XGBoost models were used to predict severe clinical course (death, discharge to hospice, invasive ventilatory support, or extracorporeal membrane oxygenation). MAIN OUTCOMES AND MEASURESPatient demographic characteristics and COVID-19 severity using the World Health Organization COVID-19 severity scale and differences between groups over time using multivariable logistic regression. RESULTSThe cohort included 174 568 adults who tested positive for SARS-CoV-2 (mean [SD] age, 44.4 [18.6] years; 53.2% female) and 1 133 848 adult controls who tested negative for SARS-CoV-2 (mean [SD] age, 49.5 [19.2] years; 57.1% female). Of the 174 568 adults with SARS-CoV-2, 32 472(18.6%) were hospitalized, and 6565 (20.2%) of those had a severe clinical course (invasive ventilatory support, extracorporeal membrane oxygenation, death, or discharge to hospice). Of the hospitalized patients, mortality was 11.6% overall and decreased from 16.4% in March to April 2020 to 8.6% in September to October 2020 (P = .002 for monthly trend). Using 64 inputs available on the first hospital day, this study predicted a severe clinical course using random forest and XGBoost models (area under the receiver operating curve = 0.87 for both) that were stable over time. The factor most strongly associated with clinical severity was pH; this result was consistent across machine learning methods. In a separate multivariable logistic regression model built for inference, (continued) Key Points Question In a US data resource large enough to adjust for multiple confounders, what risk factors are associated with COVID-19 severity and severity trajectory over time, and can machine learning models predict clinical severity? Findings In this cohort study of 174 568 adults with SARS-CoV-2, 32 472 (18.6%) were hospitalized and 6565 (20.2%) were severely ill, and first-day machine learning models accurately predicted clinical severity. Mortality was 11.6%

BackgroundDelirium is a common severe neuropsychiatric condition secondary to physical illness, which predominantly affects older adults in hospital. Prior to this study, the UK point prevalence of delirium was unknown. We set out to ascertain the point prevalence of delirium across UK hospitals and how this relates to adverse outcomes.MethodsWe conducted a prospective observational study across 45 UK acute care hospitals. Older adults aged 65 years and older were screened and assessed for evidence of delirium on World Delirium Awareness Day (14th March 2018). We included patients admitted within the previous 48 h, excluding critical care admissions.ResultsThe point prevalence of Diagnostic and Statistical Manual on Mental Disorders, Fifth Edition (DSM-5) delirium diagnosis was 14.7% (222/1507). Delirium presence was associated with higher Clinical Frailty Scale (CFS): CFS 4–6 (frail) (OR 4.80, CI 2.63–8.74), 7–9 (very frail) (OR 9.33, CI 4.79–18.17), compared to 1–3 (fit). However, higher CFS was associated with reduced delirium recognition (7–9 compared to 1–3; OR 0.16, CI 0.04–0.77). In multivariable analyses, delirium was associated with increased length of stay (+ 3.45 days, CI 1.75–5.07) and increased mortality (OR 2.43, CI 1.44–4.09) at 1 month. Screening for delirium was associated with an increased chance of recognition (OR 5.47, CI 2.67–11.21).ConclusionsDelirium is prevalent in older adults in UK hospitals but remains under-recognised. Frailty is strongly associated with the development of delirium, but delirium is less likely to be recognised in frail patients. The presence of delirium is associated with increased mortality and length of stay at one month. A national programme to increase screening has the potential to improve recognition.